Belief Propagation Reloaded: Learning BP-Layers for Labeling Problems

13 Mar 2020Patrick KnöbelreiterChristian SormannAlexander ShekhovtsovFriedrich FraundorferThomas Pock

It has been proposed by many researchers that combining deep neural networks with graphical models can create more efficient and better regularized composite models. The main difficulties in implementing this in practice are associated with a discrepancy in suitable learning objectives as well as with the necessity of approximations for the inference... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.